Paper
15 October 1986 Hierarchical Structures, Parallelism And Planning In Analyzing Time-Varying Images
C. L. Tan, W. N. Martin
Author Affiliations +
Proceedings Volume 0638, Hybrid Image Processing; (1986) https://doi.org/10.1117/12.964275
Event: 1986 Technical Symposium Southeast, 1986, Orlando, United States
Abstract
A paradigm to reduce computational costs in analyzing time-varying images is proposed in this paper. Our model is a hybrid of three recent advances in computer science, namely, hierarchical data structures, parallel processing, and heuristic planning. A pipelined pyramid image structure is constructed in the model by continually converging incoming images into successively lower resolutions. The model also contains a set of processors which work concurrently and asynchronously on subimages at different levels of this pyramid structure. These processors initially watch for interesting features in the lowest resolution rendition, of the scene. Processors working on promising areas individually but coopeiatively proceed to progressively higher resolution levels according to a planning scheme. This distributed planning mechanism is afforded through a blackboard control structure which also permits a unified scene interpretation. The model has been implemented in a simulated distributed system.
© (1986) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
C. L. Tan and W. N. Martin "Hierarchical Structures, Parallelism And Planning In Analyzing Time-Varying Images", Proc. SPIE 0638, Hybrid Image Processing, (15 October 1986); https://doi.org/10.1117/12.964275
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KEYWORDS
Image processing

Image resolution

Image analysis

Motion analysis

Motion models

Data modeling

Machine vision

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